Thanks Jeff, I am a little disappointed when you said the guarantee are even weeker.But I will take a look on this and try to understand what is really done.
Le 13 déc. 2017 18:18, "Jeff Jirsa" <jji...@gmail.com> a écrit : Entry point is here: https://github.com/apache/cassandra/blob/trunk/ src/java/org/apache/cassandra/cql3/statements/BatchStatement.java#L346 , which will call through to https://github.com/apache/ cassandra/blob/trunk/src/java/org/apache/cassandra/service/ StorageProxy.java#L938-L953 I believe the guarantees are weaker than the blog suggests, but it's nuanced, and a lot of these types of questions come down to data model (you can model it in a way that you can avoid problems with weaknesses in isolation, but that requires a detailed explanation of your use case, etc). On Wed, Dec 13, 2017 at 8:56 AM, Mickael Delanoë <delanoe...@gmail.com> wrote: > Hi Nicolas, > Thanks for you answer. > Is your assumption 100% sure ? > Because the few test I did - using nodetools getendpoints - shown that the > data for the two tables when I used the same partition key went to the same > "nodes" . So I would have expected cassandra to be smart enough to apply > them in the memtable in a single operation to achieve the isolation as the > whole batch will be executed on a single node. > Does anybody know where I can find, where the batch operations are > processed in the Cassandra source code, so I could check how all this is > processed ? > > Regards, > Mickaël > > > > 2017-12-13 11:18 GMT+01:00 Nicolas Guyomar <nicolas.guyo...@gmail.com>: > >> Hi Mickael, >> >> Partition are related to the table they exist in, so in your case, you >> are targeting 2 partitions in 2 different tables. >> Therefore, IMHO, you will only get atomicity using your batch statement >> >> On 11 December 2017 at 15:59, Mickael Delanoë <delanoe...@gmail.com> >> wrote: >> >>> Hello, >>> >>> I have a question regarding batch isolation and atomicity with query >>> using a same partition key. >>> >>> The Datastax documentation says about the batches : >>> "Combines multiple DML statements to achieve atomicity and isolation >>> when targeting a single partition or only atomicity when targeting multiple >>> partitions. A batch applies all DMLs within a single partition before the >>> data is available, ensuring atomicity and isolation."" >>> >>> But I try to find exactly what can be considered as a "single partition" >>> and I cannot find a clear response yet. The examples and explanations >>> always speak about partition with only one table used inside the batch. My >>> concern is about partition when we use different table in a batch. So I >>> would like some clarification. >>> >>> Here is my use case, I have 2 tables with the same partition-key which >>> is "user_id" : >>> >>> CREATE TABLE tableA ( >>> user_id text, >>> clustering text, >>> value text, >>> PRIMARY KEY (user_id, clustering)); >>> >>> CREATE TABLE tableB ( >>> user_id text, >>> clustering1 text, >>> clustering2 text, >>> value text, >>> PRIMARY KEY (user_id, clustering1, clustering2)); >>> >>> If I do a batch query like this : >>> >>> BEGIN BATCH >>> INSERT INTO tableA (user_id, clustering, value) VALUES ('1234', 'c1', >>> 'val1'); >>> INSERT INTO tableB (user_id, clustering1, clustering1, value) VALUES >>> ('1234', 'cl1', 'cl2', 'avalue'); >>> APPLY BATCH; >>> >>> the DML statements uses the same partition-key, can we say they are >>> targetting the same partition or, as the partition key are for different >>> table, should we consider this is different partition? And so does this >>> batch ensure atomicity and isolation (in the sense described in Datastax >>> doc)? Or only atomicity? >>> >>> Thanks for you help, >>> Mickaël Delanoë >>> >> >> > > > -- > Mickaël Delanoë >
